Rising patient demand and escalating operational costs are placing unprecedented pressure on healthcare systems worldwide. At the same time, healthcare organisations are managing an ever-growing volume of data - from electronic health records (EHRs) and medical imaging to patient-generated health information. Despite this vast data landscape, much of the information remains siloed and underutilised, limiting healthcare providers’ ability to unlock its full potential to improve patient outcomes and operational efficiency.
To keep pace with these challenges and continue delivering quality care, healthcare organisations must embrace smarter technology solutions. Central to this is breaking down data silos, improving access to critical information, and leveraging AI-driven tools to support better decision-making and streamline workflows.
The healthcare sector is experiencing significant strain from several key trends that are reshaping how care is delivered and how systems must operate:
In 2022–23, Australia spent approximately $252.5 billion on health goods and services, accounting for 9.9% of GDP, with labour costs driving over half of recurrent spending (Source: Australian Institute of Health and Welfare, Health Expenditure Overview 2022–23; Australian Productivity Commission, Health Workforce Report).
According to the Australian Digital Health Agency’s 2023–24 Annual Report, documents in My Health Record increased by 23%, now totalling 6 billion, including over 1.3 billion uploads from healthcare providers and consumers.
These trends highlight the growing complexity of healthcare systems and underscore the urgent need for technologies that can address both operational pressures and data challenges.
With growing demand and rising costs, healthcare organisations are prioritising efficiency like never before. Achieving this requires embracing AI-driven solutions that optimise workflows, reduce operational expenses, and free up time for clinicians to focus on patient care.
However, to realise the full benefits of these technologies, organisations must first overcome the challenge of fragmented data. Breaking down silos, improving data accessibility, and enabling more informed decision-making are essential steps in transforming healthcare delivery.
Despite the vast opportunities AI and data present, many healthcare providers continue to wrestle with data silos, interoperability issues, and administrative burdens that detract from their primary mission - delivering quality patient care.
Drawing on our experience working closely with healthcare providers, we have identified three key areas that consistently hinder operational efficiency and impact patient care. These challenges; medical coding, medical records management, and administrative workflows; are widely recognised pain points in the sector. Understanding these issues is essential to unlocking the benefits of AI and data-driven solutions.
Clinical coding is vital for billing, reporting, and compliance but remains a manual and time-intensive process. Healthcare professionals often spend between 35-50% of their administrative time on tasks such as coding, detracting from direct patient care. The manual nature of coding introduces errors that can lead to inaccurate billing, rejected claims, and delayed reimbursements.
Adding to the complexity, multiple coding systems - like ICD-10, CPT, and the emerging ICD-11 - vary across regions and institutions, complicating data sharing and analysis. Constant updates and evolving regulations further burden organisations, increasing the risk of non-compliance and costly penalties.
Fragmentation remains a major issue in electronic medical record (EMR) systems. Many providers operate multiple disconnected platforms, making it difficult for clinicians to access complete and current patient data when it’s needed most. This fragmentation can delay diagnosis, cause redundant testing, and ultimately compromise patient outcomes.
Interoperability problems persist despite advances in digital health, with systems failing to exchange data efficiently. Clinicians often spend around 34% of their time on documentation, leading to fatigue and burnout. Manual data entry errors further threaten patient safety and care quality.
Healthcare professionals are spending a disproportionate amount of time on non-clinical tasks such as scheduling, billing, and data entry - activities that divert focus from patient-facing care. Physicians, for example, may spend only 27% of their time with patients, with the remainder consumed by administrative work.
Outdated workflows and manual handoffs create bottlenecks that delay service delivery and lower productivity. Redundant documentation requirements add to this inefficiency, contributing to staff burnout and higher turnover rates.
Healthcare organisations are increasingly turning to AI and cloud technologies to tackle their most pressing challenges. These innovations not only improve operational efficiency but also enhance the quality of patient care by streamlining workflows and providing better data accessibility.
Clinical coding is essential yet time-consuming and prone to error. AI-powered tools, leveraging Natural Language Processing (NLP), can automatically analyse clinical notes and assign accurate codes. This reduces the administrative burden, accelerates billing cycles, and minimises costly errors.
Standardising coding through AI also promotes consistency across different systems, helping healthcare organisations improve claim processing and compliance. Ultimately, automating coding frees clinical staff to spend more time with patients, improving satisfaction and care quality.
Fragmented EMRs hinder timely access to critical patient information. AI and cloud platforms such as AWS HealthLake, combined with interoperability standards like FHIR (Fast Healthcare Interoperability Resources), enable the creation of unified, accessible patient records.
These integrated systems provide clinicians with real-time, comprehensive views of patient data, improving decision-making and reducing delays. AI can further assist by highlighting anomalies, suggesting treatment options, and supporting clinical decisions—resulting in safer, more effective care.
A significant portion of clinicians’ time is spent on repetitive administrative tasks that detract from patient care. AI-driven automation can optimise scheduling, streamline billing, and automate data entry, reducing errors and speeding up processes.
Cloud-based solutions enable seamless integration of these tools, offering scalable and flexible workflows that grow with healthcare organisations. By reducing operational costs and clinician workload, automation improves staff morale and allows healthcare professionals to focus on what matters most - delivering quality care.
AI-powered automation of medical coding and cloud-based record management drastically reduces manual workloads. This frees clinicians to devote more time to direct patient care and speeds up processes like clinical documentation and claims submission.
By standardising coding practices and utilising AI-driven validation tools, healthcare providers reduce billing errors and ensure adherence to regulations such as ICD-10 and CPT. This improves claim acceptance rates and accelerates reimbursement cycles.
Cloud platforms like AWS HealthLake and the adoption of interoperability standards such as FHIR enable seamless data sharing. Clinicians gain access to comprehensive, real-time patient information, supporting collaboration and more informed decisions.
AI platforms, including Amazon SageMaker, analyse clinical data to generate actionable insights. These insights help healthcare professionals make faster, evidence-based decisions that improve patient outcomes and operational efficiency.
Automation of scheduling, billing, and data entry tasks lowers administrative overhead and reduces errors. Healthcare organisations optimise resource allocation, cut down on unnecessary non-clinical work, and improve overall cost efficiency.
By freeing clinicians from administrative burdens, AI-driven solutions allow for more meaningful patient interactions. Enhanced decision support tools also contribute to more accurate diagnoses and better treatment plans, boosting patient satisfaction.
Cloud solutions like AWS HealthLake scale with organisational growth, handling increasing volumes of healthcare data. This flexibility ensures long-term sustainability and adaptability to evolving technology and care delivery models.
Automating routine tasks alleviates the administrative load on clinicians, improving job satisfaction and reducing burnout. This supports staff retention and promotes a healthier workforce focused on patient care.
Healthcare is facing significant challenges - from rising patient demand and escalating costs to managing vast and fragmented data. Yet, these pressures also create an opportunity for transformation. AI and data-driven solutions are no longer just emerging technologies; they are essential tools that enable healthcare organisations to improve operational efficiency, enhance patient care, and reduce clinician burnout.
By automating clinical coding, unifying medical records, and streamlining administrative workflows, these technologies free healthcare professionals to focus on what matters most -delivering quality care. As the healthcare landscape continues to evolve, embracing AI and cloud strategies will be critical to staying ahead and achieving sustainable growth.
At Infostatus, we understand the unique challenges healthcare organisations face in this dynamic environment. That’s why we offer our Cloud Insights Assessment (CIA), tailored specifically to the healthcare sector. This comprehensive assessment provides a clear view of your current cloud maturity and uncovers opportunities to enhance your AI strategy, data management, and operational workflows.
Our CIA goes beyond theory - by identifying real-world gaps and potential improvements, we provide practical, actionable recommendations to optimise your cloud infrastructure and fully leverage AI and data technologies.
Start the conversation today. Book your complimentary Cloud Insights Assessment and discover how AI, data, and cloud can transform your healthcare operations for better outcomes and greater efficiency.